With the rapid development of technology, programming languages have become an indispensable part of modern society:
Be it website development, mobile apps, artificial intelligence or embedded systems, programming languages play a key role.
Most of the currently popular AI artificial intelligence is implemented through the Python language.
As the basic language of the AI technology framework, Python can be dynamically compiled compared to other programming languages. It not only has high development efficiency, but can also build networks and process data.
Simple syntax and versatility in multiple scenarios have made Python the most popular programming language in recent years.
Likewise, SQL (Structured Query Language) is a programming language used to store and process information in a relational database.
SQL allows users to perform a variety of operations, including querying data, inserting, updating, deleting data, and defining and managing database structures.
Through SQL, users can easily interact with the database to achieve data storage, retrieval and maintenance. The SQL language has simple syntax and rich functionality, allowing developers to effectively manage large amounts of data.
Therefore, in this year's 10th annual top programming language list released by IEEE Spectrum, Python and SQL ranked first in trends and jobs respectively, and Python ranked first on Spectrum's list.
Interpretation of rankings
Rankings in Spectrum reflect typical IEEE members' interests and needs in programming languages.
Job categories show the programming language skills currently required for relevant jobs, and trends represent programming languages that are particularly popular or valued today.
Python's dominance among programming languages has increased largely at the expense of smaller, more specialized languages.
Python has become a "jack of all trades" programming language and excels in certain areas.
For example, in the field of artificial intelligence: powerful and extensive libraries make Python ubiquitous.
While Moore's Law is waning in high-end computing, low-end microcontrollers are still benefiting from performance improvements, meaning there's now enough computing power on a 70-cent CPU.
Python has become a competitive choice in embedded development.
In the long run, Python's position is also constantly consolidated:
Many children and teenagers are now using Python to write their first game or control their first LED.
This helps them seamlessly move into more advanced fields and even find jobs using the same programming language.
But just mastering Python is not enough to fully meet career needs.
In the ranking of "jobs" on the list, SQL tops the list. This is because in today's distributed architecture, large amounts of business-critical data are stored in SQL databases.
If you want to do anything with this information, you have to know how to get it.
But the irony is that it's hard to find a job as a pure SQL programmer. Employers like to see SQL skills combined with other languages such as Java or C++.
On the other hand, although Python has become the unquestionable number one in the current trend in the rankings, programming is far from becoming a single culture.
Java and various C-like languages combined have surpassed Python in popularity, especially in high-performance or resource-sensitive tasks.
Because Python's interpreter overhead is too expensive (despite many attempts to make Python more competitive in this regard), there are also software ecosystems that are not easily integrated into Python for other reasons.
For example, R is a language for statistical analysis and visualization that came to prominence a few years ago with the rise of big data.
Although the R language is powerful, it is not easy to learn. Its syntax is arcane, and functions are often performed on entire vectors, lists, and other high-level data structures.
Although there are Python libraries that provide similar analysis and graphics capabilities, the R language remains popular because of its specificity, which also makes R scripts difficult to port.
This is a significant issue given that a large amount of statistical analysis and academic research is based on the R language.
This situation is similar to Fortran. In Fortran, the value of existing verification code for physics simulations and other scientific calculations has always exceeded the costs associated with using one of the oldest programming languages in existence.
Even today, people can still find jobs as Fortran programmers. But the job may require a security clearance, as these jobs are primarily at U.S. federal defense or energy laboratories, such as Oak Ridge National Laboratory.
If you can't get a security clearance, but still prefer a programming language with some history, Cobol is another possible option.
This is for similar reasons to Fortran: because there are large installed bases of code that work well even when errors are costly.
Many large banks still need Cobol programmers, and in fact there are more fintech developer positions on the market looking for Cobol masters than there are positions in the cryptocurrency space.
These older languages may also appear in unexpected places. For example, Ladder Logic was originally created for industrial control applications and is usually associated with old-fashioned technology.
However, one of the notable emerging aerospace companies, Blue Origin, has posted jobs requiring Ladder Logic skills.
This may be related to the cluster of ground equipment needed to fuel, power and test the booster and spacecraft.
It can be seen that although Python is the current mainstream programming, Java and C languages still have their own advantages, and some old languages are irreplaceable.
Different programming languages meet different needs, and maintaining diversity is crucial.
Finally, I would like to thank everyone who reads my article carefully. Reciprocity is always necessary. Although the following information is not very valuable, you can take it directly if you can use it:
